Indexed on: 06 Aug '08Published on: 06 Aug '08Published in: Langmuir
Inverse gas chromatography (IGC) is a widely used method for determining the dispersive component of the surface energy (gamma s (d)) of particulate and fibrous solids. Such measurements are normally conducted at very low solute concentrations (infinite dilution), and they result in a single numerical value of gamma s (d) for homogeneous materials which exhibit Henry's Law adsorption behavior. However, many real solid surfaces are heterogeneous and this may be demonstrated by the nonlinear isotherms obtained at low solute surface coverages resulting in reported gamma s (d) values which are not unique. This paper presents a new method for determining of gamma s (d) distributions as a function of the solute surface coverage using adsorption isosteres for an homologous series of hydrocarbon adsorbates. gamma s (d) distributions reported here were successfully determined using two different solid materials (glass beads and alumina particles) up to typical surface coverages of approximately 10% and clearly show significant variations in gamma s (d) with solute surface coverage. The effects of sample aging and pretreatment also exhibited clear differences in the gamma s (d) distributions obtained. gamma s (d) was determined using both the Dorris-Gray and Schultz methods, with the Dorris-Gray method exhibiting a much lower experimental error. It was established that the errors associated with this statistical measurement of surface energy were strongly dependent on the quality of the experimental data sets obtained. R (2) for the linearity of fit of the retention data to the Dorris-Gray gamma s (d) analysis was found to be a valid criterion for predicting the robustness of gamma s (d) distributions obtained. Detailed discussions of other critical experimental and analysis factors relevant to this methodology, as well as the reproducibility of gamma s (d) profiles are also presented. This paper establishes that IGC can be used for determining the gamma s (d) distributions of particulate solids and is demonstrated that this method is very useful way for studying the surface energy heterogeneity of complex particulate solids.